LIVA Z5 [Win 11] ECS RPLU-MINI
Geekbench AI Score
2059
Single Precision Score
2067
Half Precision Score
1312
Quantized Score
Geekbench AI 1.7.0 for Windows AVX2
Result Information
| User | Tungsten |
| Upload Date | March 29 2026 09:10 AM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Intel(R) UHD Graphics |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | ECS RPLU-MINI |
| Motherboard | ECS RPLU-MINI |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i3-1315U |
| Topology | 1 Processor, 6 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 186 Stepping 3 |
| Base Frequency | 1.20 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
892
165.8 IPS |
|
|
Image Classification (HP)
|
100% |
879
163.6 IPS |
|
|
Image Classification (Q)
|
100% |
741
137.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
1295
21.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
1491
24.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
963
15.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
7172
8.37 IPS |
|
|
Pose Estimation (HP)
|
100% |
8273
9.65 IPS |
|
|
Pose Estimation (Q)
|
96% |
4089
4.79 IPS |
|
|
Object Detection (SP)
|
100% |
1020
80.9 IPS |
|
|
Object Detection (HP)
|
98% |
880
70.0 IPS |
|
|
Object Detection (Q)
|
86% |
853
68.6 IPS |
|
|
Face Detection (SP)
|
100% |
1964
23.3 IPS |
|
|
Face Detection (HP)
|
100% |
2334
27.7 IPS |
|
|
Face Detection (Q)
|
97% |
1432
17.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
4115
31.7 IPS |
|
|
Depth Estimation (HP)
|
98% |
4564
35.3 IPS |
|
|
Depth Estimation (Q)
|
77% |
2891
23.2 IPS |
|
|
Style Transfer (SP)
|
100% |
15853
20.4 IPS |
|
|
Style Transfer (HP)
|
100% |
20677
26.6 IPS |
|
|
Style Transfer (Q)
|
98% |
10342
13.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2379
87.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3100
114.5 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
1083
40.1 IPS |
|
|
Text Classification (SP)
|
100% |
733
977.8 IPS |
|
|
Text Classification (HP)
|
100% |
321
427.9 IPS |
|
|
Text Classification (Q)
|
97% |
348
466.4 IPS |
|
|
Machine Translation (SP)
|
100% |
727
12.5 IPS |
|
|
Machine Translation (HP)
|
100% |
682
11.7 IPS |
|
|
Machine Translation (Q)
|
70% |
379
7.12 IPS |
